Overview

Dataset statistics

Number of variables5
Number of observations23
Missing cells3
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory46.7 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구 서점현황에 대한 데이터입니다.서점명, 도로명주소, 전화번호, 위도, 경도 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087027&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 3 (13.0%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:46:01.816559
Analysis finished2024-03-18 04:46:04.270428
Duration2.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-03-18T13:46:04.356426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2024-03-18T13:46:04.490535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

상호명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-18T13:46:04.665460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.6086957
Min length3

Characters and Unicode

Total characters129
Distinct characters64
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row대학서적 인하대
2nd row영풍문고 인천터미널점
3rd row학산서점
4th row사람과공간딴뚬꽌뚬
5th row푸라하
ValueCountFrequency (%)
대학서적 1
 
3.4%
중고책매장 1
 
3.4%
대영교육도서 1
 
3.4%
지학사 1
 
3.4%
성이서점문구 1
 
3.4%
문학점 1
 
3.4%
도트원 1
 
3.4%
이츠북 1
 
3.4%
문우서적 1
 
3.4%
상문도서 1
 
3.4%
Other values (19) 19
65.5%
2024-03-18T13:46:04.971495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 14
 
10.9%
점 9
 
7.0%
6
 
4.7%
대 5
 
3.9%
인 5
 
3.9%
학 5
 
3.9%
문 5
 
3.9%
도 4
 
3.1%
사 4
 
3.1%
천 3
 
2.3%
Other values (54) 69
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
95.3%
Space Separator 6
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 14
 
11.4%
점 9
 
7.3%
대 5
 
4.1%
인 5
 
4.1%
학 5
 
4.1%
문 5
 
4.1%
도 4
 
3.3%
사 4
 
3.3%
천 3
 
2.4%
이 3
 
2.4%
Other values (53) 66
53.7%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
95.3%
Common 6
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 14
 
11.4%
점 9
 
7.3%
대 5
 
4.1%
인 5
 
4.1%
학 5
 
4.1%
문 5
 
4.1%
도 4
 
3.3%
사 4
 
3.3%
천 3
 
2.4%
이 3
 
2.4%
Other values (53) 66
53.7%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
95.3%
ASCII 6
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 14
 
11.4%
점 9
 
7.3%
대 5
 
4.1%
인 5
 
4.1%
학 5
 
4.1%
문 5
 
4.1%
도 4
 
3.3%
사 4
 
3.3%
천 3
 
2.4%
이 3
 
2.4%
Other values (53) 66
53.7%
ASCII
ValueCountFrequency (%)
6
100.0%

지번주소
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-18T13:46:05.142599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length21.304348
Min length18

Characters and Unicode

Total characters490
Distinct characters51
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)87.0%

Sample

1st row인천광역시 미추홀구 용현동 253
2nd row인천광역시 미추홀구 관교동 15 인천터미널 지하1층
3rd row인천광역시 미추홀구 학익동 209-3
4th row인천광역시 미추홀구 주안동 468-1
5th row인천광역시 미추홀구 주안동 438-39 단독1층
ValueCountFrequency (%)
인천광역시 23
23.5%
미추홀구 23
23.5%
도화동 9
 
9.2%
주안동 4
 
4.1%
969 3
 
3.1%
학익동 3
 
3.1%
관교동 2
 
2.0%
용현동 2
 
2.0%
문학동 2
 
2.0%
36-1 1
 
1.0%
Other values (26) 26
26.5%
2024-03-18T13:46:05.545048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
15.3%
인 24
 
4.9%
미 24
 
4.9%
천 24
 
4.9%
광 23
 
4.7%
역 23
 
4.7%
시 23
 
4.7%
추 23
 
4.7%
홀 23
 
4.7%
구 23
 
4.7%
Other values (41) 205
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 295
60.2%
Decimal Number 100
 
20.4%
Space Separator 75
 
15.3%
Dash Punctuation 18
 
3.7%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 24
 
8.1%
미 24
 
8.1%
천 24
 
8.1%
광 23
 
7.8%
역 23
 
7.8%
시 23
 
7.8%
추 23
 
7.8%
홀 23
 
7.8%
구 23
 
7.8%
동 23
 
7.8%
Other values (27) 62
21.0%
Decimal Number
ValueCountFrequency (%)
1 18
18.0%
6 13
13.0%
4 12
12.0%
9 11
11.0%
8 9
9.0%
0 9
9.0%
5 8
8.0%
3 8
8.0%
2 8
8.0%
7 4
 
4.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 295
60.2%
Common 195
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 24
 
8.1%
미 24
 
8.1%
천 24
 
8.1%
광 23
 
7.8%
역 23
 
7.8%
시 23
 
7.8%
추 23
 
7.8%
홀 23
 
7.8%
구 23
 
7.8%
동 23
 
7.8%
Other values (27) 62
21.0%
Common
ValueCountFrequency (%)
75
38.5%
1 18
 
9.2%
- 18
 
9.2%
6 13
 
6.7%
4 12
 
6.2%
9 11
 
5.6%
8 9
 
4.6%
0 9
 
4.6%
5 8
 
4.1%
3 8
 
4.1%
Other values (4) 14
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
60.2%
ASCII 195
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
38.5%
1 18
 
9.2%
- 18
 
9.2%
6 13
 
6.7%
4 12
 
6.2%
9 11
 
5.6%
8 9
 
4.6%
0 9
 
4.6%
5 8
 
4.1%
3 8
 
4.1%
Other values (4) 14
 
7.2%
Hangul
ValueCountFrequency (%)
인 24
 
8.1%
미 24
 
8.1%
천 24
 
8.1%
광 23
 
7.8%
역 23
 
7.8%
시 23
 
7.8%
추 23
 
7.8%
홀 23
 
7.8%
구 23
 
7.8%
동 23
 
7.8%
Other values (27) 62
21.0%

도로명주소
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-18T13:46:05.726758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length33
Mean length22.173913
Min length18

Characters and Unicode

Total characters510
Distinct characters77
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)87.0%

Sample

1st row인천광역시 미추홀구 인하로 100
2nd row인천광역시 미추홀구 연남로 35 인천터미널 지하1층
3rd row인천광역시 미추홀구 매소홀로 355
4th row인천광역시 미추홀구 경인로 358 사람과공간 Bldg. 지하 1층
5th row인천광역시 미추홀구 미추홀대로658번길 14-19 단독1층
ValueCountFrequency (%)
인천광역시 23
22.1%
미추홀구 23
22.1%
봉수대로 3
 
2.9%
17 3
 
2.9%
매소홀로 2
 
1.9%
숙골로 2
 
1.9%
석정로 2
 
1.9%
1층 2
 
1.9%
188 1
 
1.0%
인하로 1
 
1.0%
Other values (42) 42
40.4%
2024-03-18T13:46:06.042789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
15.9%
1 28
 
5.5%
인 27
 
5.3%
홀 27
 
5.3%
미 26
 
5.1%
추 25
 
4.9%
구 24
 
4.7%
천 24
 
4.7%
광 23
 
4.5%
역 23
 
4.5%
Other values (67) 202
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
64.7%
Decimal Number 87
 
17.1%
Space Separator 81
 
15.9%
Dash Punctuation 4
 
0.8%
Lowercase Letter 3
 
0.6%
Uppercase Letter 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 27
 
8.2%
홀 27
 
8.2%
미 26
 
7.9%
추 25
 
7.6%
구 24
 
7.3%
천 24
 
7.3%
광 23
 
7.0%
역 23
 
7.0%
시 23
 
7.0%
로 21
 
6.4%
Other values (48) 87
26.4%
Decimal Number
ValueCountFrequency (%)
1 28
32.2%
8 9
 
10.3%
3 8
 
9.2%
2 8
 
9.2%
0 7
 
8.0%
7 7
 
8.0%
4 7
 
8.0%
6 6
 
6.9%
5 6
 
6.9%
9 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
l 1
33.3%
d 1
33.3%
g 1
33.3%
Space Separator
ValueCountFrequency (%)
81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 330
64.7%
Common 175
34.3%
Latin 5
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 27
 
8.2%
홀 27
 
8.2%
미 26
 
7.9%
추 25
 
7.6%
구 24
 
7.3%
천 24
 
7.3%
광 23
 
7.0%
역 23
 
7.0%
시 23
 
7.0%
로 21
 
6.4%
Other values (48) 87
26.4%
Common
ValueCountFrequency (%)
81
46.3%
1 28
 
16.0%
8 9
 
5.1%
3 8
 
4.6%
2 8
 
4.6%
0 7
 
4.0%
7 7
 
4.0%
4 7
 
4.0%
6 6
 
3.4%
5 6
 
3.4%
Other values (5) 8
 
4.6%
Latin
ValueCountFrequency (%)
B 2
40.0%
l 1
20.0%
d 1
20.0%
g 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 330
64.7%
ASCII 180
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
45.0%
1 28
 
15.6%
8 9
 
5.0%
3 8
 
4.4%
2 8
 
4.4%
0 7
 
3.9%
7 7
 
3.9%
4 7
 
3.9%
6 6
 
3.3%
5 6
 
3.3%
Other values (9) 13
 
7.2%
Hangul
ValueCountFrequency (%)
인 27
 
8.2%
홀 27
 
8.2%
미 26
 
7.9%
추 25
 
7.6%
구 24
 
7.3%
천 24
 
7.3%
광 23
 
7.0%
역 23
 
7.0%
시 23
 
7.0%
로 21
 
6.4%
Other values (48) 87
26.4%

전화번호
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing3
Missing (%)13.0%
Memory size316.0 B
2024-03-18T13:46:06.238934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.4
Min length12

Characters and Unicode

Total characters248
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row032-868-9667
2nd row032-422-5900
3rd row032-875-3151
4th row0507-1329-8624
5th row0507-1352-3268
ValueCountFrequency (%)
032-422-5900 1
 
5.0%
032-875-3151 1
 
5.0%
032-772-1333 1
 
5.0%
032-763-1462 1
 
5.0%
032-442-4573 1
 
5.0%
032-887-0777 1
 
5.0%
032-762-4523 1
 
5.0%
032-424-6050 1
 
5.0%
032-862-4033 1
 
5.0%
032-770-8147 1
 
5.0%
Other values (10) 10
50.0%
2024-03-18T13:46:06.536192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 40
16.1%
0 36
14.5%
3 33
13.3%
2 33
13.3%
7 23
9.3%
4 18
7.3%
1 17
6.9%
5 16
 
6.5%
8 15
 
6.0%
6 13
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
83.9%
Dash Punctuation 40
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36
17.3%
3 33
15.9%
2 33
15.9%
7 23
11.1%
4 18
8.7%
1 17
8.2%
5 16
7.7%
8 15
7.2%
6 13
 
6.2%
9 4
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 40
16.1%
0 36
14.5%
3 33
13.3%
2 33
13.3%
7 23
9.3%
4 18
7.3%
1 17
6.9%
5 16
 
6.5%
8 15
 
6.0%
6 13
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 40
16.1%
0 36
14.5%
3 33
13.3%
2 33
13.3%
7 23
9.3%
4 18
7.3%
1 17
6.9%
5 16
 
6.5%
8 15
 
6.0%
6 13
 
5.2%

Interactions

2024-03-18T13:46:03.852767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:46:06.615409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0001.0000.9410.9411.000
상호명1.0001.0001.0001.0001.000
지번주소0.9411.0001.0001.0001.000
도로명주소0.9411.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-03-18T13:46:04.077934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:46:04.201129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번상호명지번주소도로명주소전화번호
01대학서적 인하대인천광역시 미추홀구 용현동 253인천광역시 미추홀구 인하로 100032-868-9667
12영풍문고 인천터미널점인천광역시 미추홀구 관교동 15 인천터미널 지하1층인천광역시 미추홀구 연남로 35 인천터미널 지하1층032-422-5900
23학산서점인천광역시 미추홀구 학익동 209-3인천광역시 미추홀구 매소홀로 355032-875-3151
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